Predicting the possibility of African horse sickness (AHS) introduction into China using spatial risk analysis and habitat connectivity of Culicoides

Gao, Shan; Zeng, Zan; Wang, Haoning; Chen, Fangyuan; Huang, Liang; Wang, Xiaolong

doi:10.1038/s41598-022-07512-w

Cited by 12 publications

(17 citation statements)

References 45 publications

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“…China's cross-border trade is developing at a fast pace, but the constraints of real factors such as capital, scale, and management level directly lead to the dilemma that Chinese cross-border e-merchants generally face high costs in the settlement link, poor timeliness, and difficulty in repayment [3]. While being highly valued, the instability and high failure rate of alliances make enterprises have to weigh the benefits and risks when joining them [4]. In addition, the lack of sufficient funds to build a modern information management system has led to "indigestion" and order loss in most logistics enterprises from time to time.…”

Section: Introductionmentioning

confidence: 99%

E-Commerce across Boarder Logistics Risk Evaluation Model Based on Improved Neural Network

Qiao

2022

Journal of Function Spaces

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BP neural network is a typical algorithm in artificial intelligence network. It has strong nonlinear mapping ability and is the most prominent part to solve some nonlinear problems. In the traditional BP algorithm, the coincidence initialization of weights and thresholds is random, which reduces the efficiency of the algorithm on the one hand and affects the accuracy of the algorithm results on the other hand. In order to solve these problems, this paper studies an e-commerce cross-border logistics risk assessment model based on improved neural network. This model can help merchants engaged in cross-border e-commerce to select appropriate third-party settlement platforms, so as to reduce the cost of merchants in the process of capital settlement. The key information in BP neural network algorithm is stored in weights and thresholds, which is enough to prove the importance of weights and thresholds for the effective operation of the whole network. The e-commerce cross-border logistics risk assessment model based on improved neural network aims to solve the problem of low level of risk assessment and the bottleneck of logistics risk assessment. The improved e-commerce cross-border logistics risk assessment model based on neural network can be used for risk rating before business development, so as to adopt different risk management methods for different risk levels.

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Section: Introductionmentioning

confidence: 99%

E-Commerce across Boarder Logistics Risk Evaluation Model Based on Improved Neural Network

Qiao

2022

Journal of Function Spaces

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“…We filtered the presence points using the SDM Toolbox v1.1c [ 26 ] integrated in ArcGIS 10.6 to minimize potential spatial autocorrelation [ 27 ]. Filtering was performed by limiting the minimum distance between each pair of occurrence points at 10 km [ 28 , 29 ]. This helped to address problems associated with spatial sampling biases.…”

Section: Methodsmentioning

confidence: 99%

Spatial modeling and ecological suitability of monkeypox disease in Southern Nigeria

Arotolu

Afe²,

Wang³

et al. 2022

PLoS ONE

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The reemergence of monkeypoxvirus (MPXV) in 2017 after about 39 years of no reported cases in Nigeria, and the recent incidence in countries such as the United States of America, United Kingdom, Singapore, and Israel which have been reportedly linked with travelers from Africa, have heightened concern that MPXV may have emerged to occupy the vacant ecological and immunological niche created by the extinct smallpox virus. This study was carried out to identify environmental conditions and areas that are environmentally suitable (risky areas) for MPXV in southern Nigeria. One hundred and sixteen (116) spatially unique MPXV occurrence data from 2017–2021 and corresponding environmental variables were spatially modeled by a maximum entropy algorithm to evaluate the contribution of the variables to the distribution of the viral disease. A variance inflation analysis was adopted to limit the number of environmental variables and minimize multicollinearity. The five variables that contributed to the suitability model for MPXV disease are precipitation of driest quarter (47%), elevation (26%), human population density (17%), minimum temperature in December (7%), and maximum temperature in March (3%). For validation, our model had a high AUC value of 0.92 and standard deviation of 0.009 indicating that it had excellent ability to predict the suitable areas for monkeypox disease. Categorized risk classes across southern states was also identified. A total of eight states were predicted to be at high risk of monkeypox outbreak occurrence. These findings can guide policymakers in resources allocation and distribution to effectively implement targeted control measures for MPXV outbreaks in southern Nigeria.

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“…It is likely that the range overlap of competent Palearctic species of Culicoides with C. imicola facilitated the novel vector-pathogen interaction in the case of BTV, and there is no reason to suggest that this would not happen with AHSV as well. This concern has prompted many publications to review and assess the risk of AHS spread to disease-free regions (Thompson et al 2012, Robin et al 2016, Gao et al 2022, Grewar et al 2021, Nelson et al 2022, Starešina et al 2022).…”

Section: Vector Range Expansion and Surveillancementioning

confidence: 99%

Culicoides-borne Orbivirus epidemiology in a changing climate

Hudson,

McGregor,

Shults

et al. 2023

Journal of Medical Entomology

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Orbiviruses are of significant importance to the health of wildlife and domestic animals worldwide; the major orbiviruses transmitted by multiple biting midge (Culicoides) species include bluetongue virus, epizootic hemorrhagic disease virus, and African horse sickness virus. The viruses, insect vectors, and hosts are anticipated to be impacted by global climate change, altering established Orbivirus epidemiology. Changes in global climate have the potential to alter the vector competence and extrinsic incubation period of certain biting midge species, affect local and long-distance dispersal dynamics, lead to range expansion in the geographic distribution of vector species, and increase transmission period duration (earlier spring onset and later fall transmission). If transmission intensity is associated with weather anomalies such as droughts and wind speeds, there may be changes in the number of outbreaks and periods between outbreaks for some regions. Warmer temperatures and changing climates may impact the viral genome by facilitating reassortment and through the emergence of novel viral mutations. As the climate changes, Orbivirus epidemiology will be inextricably altered as has been seen with recent outbreaks of bluetongue, epizootic hemorrhagic disease, and African horse sickness outside of endemic areas, and requires interdisciplinary teams and approaches to assess and mitigate future outbreak threats.

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Predicting the possibility of African horse sickness (AHS) introduction into China using spatial risk analysis and habitat connectivity of Culicoides

Cited by 12 publications

References 45 publications

E-Commerce across Boarder Logistics Risk Evaluation Model Based on Improved Neural Network

E-Commerce across Boarder Logistics Risk Evaluation Model Based on Improved Neural Network

Spatial modeling and ecological suitability of monkeypox disease in Southern Nigeria

Culicoides-borne Orbivirus epidemiology in a changing climate

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